Decadal predictability of regional-scale peak winds over Europe using the Earth System Model of the Max-Planck-Institute for Meteorology

Haas, Rabea; Reyers, Mark; Pinto, Joaquim G.

doi:10.1127/metz/2015/0583

Cited by 7 publications

(11 citation statements)

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“…These findings are in line with Haas et al (2015), who evaluated the decadal predictability of regional peak winds in the MiKlip ensemble baseline1 and also found highest skill scores for short lead times. The enhanced skill scores for higher percentiles are also consistent with results by Haas et al (2015), who showed, for example, that the enhanced storminess over Central Europe in the early nineties (leading to enhanced peak winds at the surface) could be identified in the baseline1 hindcasts. Such skill is not found for lower percentiles (Haas et al, 2015; their figure 7).…”

Section: Summary and Discussionsupporting

confidence: 89%

“…The enhanced skill scores for higher percentiles are also consistent with results by Haas et al (2015), who showed, for example, that the enhanced storminess over Central Europe in the early nineties (leading to enhanced peak winds at the surface) could be identified in the baseline1 hindcasts. Such skill is not found for lower percentiles (Haas et al, 2015; their figure 7).…”

Section: Summary and Discussionsupporting

confidence: 89%

“…Predictive skill for precipitation sums could even be improved by the downscaling in their study. Haas et al (2015) evaluated the decadal predictability of peak winds on the regional scale in the MPI-ESM, using a statistical-dynamical downscaling (SDD) approach for the regionalisation. Their results showed highest skill scores for short lead times and upper gust percentiles.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, a downscaling of the global datasets to the regional scale is necessary (e.g. Mieruch et al, 2014;Haas et al, 2015). In principle, it is possible to use a dynamical downscaling (DD) approach for the regionalisation of large ensembles, depending on available computing power, storage capacities and time.…”

Section: Introductionmentioning

confidence: 99%

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Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

Moemken¹,

Reyers²,

Buldmann

et al. 2016

Tellus A: Dynamic Meteorology and Oceanography

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A B S T R A C T Decadal predictions on timescales from one year to one decade are gaining importance since this time frame falls within the planning horizon of politics, economy and society. The present study examines the decadal predictability of regional wind speed and wind energy potentials in three generations of the MiKlip ('Mittelfristige Klimaprognosen') decadal prediction system. The system is based on the global Max-Planck-Institute Earth System Model (MPI-ESM), and the three generations differ primarily in the ocean initialisation. Ensembles of uninitialised historical and yearly initialised hindcast experiments are used to assess the forecast skill for 10 m wind speeds and wind energy output (Eout) over Central Europe with lead times from one year to one decade. With this aim, a statistical-dynamical downscaling (SDD) approach is used for the regionalisation. Its added value is evaluated by comparison of skill scores for MPI-ESM large-scale wind speeds and SDD-simulated regional wind speeds. All three MPI-ESM ensemble generations show some forecast skill for annual mean wind speed and Eout over Central Europe on yearly and multi-yearly time scales. This forecast skill is mostly limited to the first years after initialisation. Differences between the three ensemble generations are generally small. The regionalisation preserves and sometimes increases the forecast skills of the global runs but results depend on lead time and ensemble generation. Moreover, regionalisation often improves the ensemble spread. Seasonal Eout skills are generally lower than for annual means. Skill scores are lowest during summer and persist longest in autumn. A large-scale westerly weather type with strong pressure gradients over Central Europe is identified as potential source of the skill for wind energy potentials, showing a similar forecast skill and a high correlation with Eout anomalies. These results are promising towards the establishment of a decadal prediction system for wind energy applications over Central Europe.

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Section: Summary and Discussionsupporting

confidence: 89%

Section: Summary and Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

Moemken¹,

Reyers²,

Buldmann

et al. 2016

Tellus A: Dynamic Meteorology and Oceanography

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“…We evaluate the performance of both the global MPI-ESM and the regional CCLM hindcasts with the following datasets. For temperature and precipitation, we consider the observational dataset E-OBS (Haylock et al, 2008) As no gridded dataset is available for wind, a CCLM simulation forced with boundary conditions from ERA40 and ERA-Interim is employed as verification dataset for wind speed. For this reanalysis-driven simulation, CCLM is applied in the same model set-up as for the regionalization of the global hindcast ensemble (see above).…”

Section: Datamentioning

confidence: 99%

Development and prospects of the regional MiKlip decadal prediction system over Europe: predictive skill, added value of regionalization, and ensemble size dependency

Reyers¹,

Feldmann²,

Mieruch³

et al. 2019

Earth Syst. Dynam.

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Abstract. The current state of development and the prospects of the regional MiKlip decadal prediction system for Europe are analysed. The MiKlip regional system consists of two 10-member hindcast ensembles computed with the global coupled model MPI-ESM-LR downscaled for the European region with COSMO-CLM to a horizontal resolution of 0.22∘ (∼25 km). Prediction skills are computed for temperature, precipitation, and wind speed using E-OBS and an ERA-Interim-driven COSMO-CLM simulation as verification datasets. Focus is given to the eight European PRUDENCE regions and to lead years 1–5 after initialization. Evidence of the general potential for regional decadal predictability for all three variables is provided. For example, the initialized hindcasts outperform the uninitialized historical runs for some key regions in Europe, particularly in southern Europe. However, forecast skill is not detected in all cases, but it depends on the variable, the region, and the hindcast generation. A comparison of the downscaled hindcasts with the global MPI-ESM-LR runs reveals that the MiKlip prediction system may distinctly benefit from regionalization, in particular for parts of southern Europe and for Scandinavia. The forecast accuracy of the MiKlip ensemble is systematically enhanced when the ensemble size is increased stepwise, and 10 members is found to be suitable for decadal predictions. This result is valid for all variables and European regions in both the global and regional MiKlip ensemble. The present results are encouraging for the development of a regional decadal prediction system.

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The regional MiKlip decadal prediction system for Europe: Hindcast skill for extremes and user‐oriented variables

Moemken

Feldmann

Pinto

et al. 2020

Intl Journal of Climatology

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Regional climate predictions for the next decade are gaining importance, as this period falls within the planning horizon of politics, economy, and society. The potential predictability of climate indices or extremes at the regional scale is of particular interest. The German MiKlip project ("mid-term climate forecast") developed the first regional decadal prediction system for Europe at 0.44 resolution, based on the regional model COSMO-CLM using global MPI-ESM simulations as boundary conditions. We analyse the skill of this regional system focussing on extremes and user-oriented variables. The considered quantities are related to temperature extremes, heavy precipitation, wind impacts, and the agronomy sector. Variables related to temperature (e.g., frost days, heat wave days) show high predictive skill (anomaly correlation up to 0.9) with very little dependence on lead-time, and the skill patterns are spatially robust. The skill patterns for precipitation-related variables (e.g., heavy precipitation days) and windbased indices (like storm days) are less skilful and more heterogeneous, particularly for the latter. Quantities related to the agronomy sector (e.g., growing degree days) show high predictive skill, comparable to temperature. Overall, we provide evidence that decadal predictive skill can be generally found at the regional scale also for extremes and user-oriented variables, demonstrating how the utility of decadal predictions can be substantially enhanced. This is a very promising first step towards impact-related modelling at the regional scale and the development of individual useroriented products for stakeholders.

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Decadal predictability of regional-scale peak winds over Europe using the Earth System Model of the Max-Planck-Institute for Meteorology

Cited by 7 publications

References 0 publications

Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

Development and prospects of the regional MiKlip decadal prediction system over Europe: predictive skill, added value of regionalization, and ensemble size dependency

The regional MiKlip decadal prediction system for Europe: Hindcast skill for extremes and user‐oriented variables

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